R语言基础

Missing from submitted HW for Research Paper Selection assignment. Exploratory statistics and their commands: 1) summary(data$x) 2) hist(data$x) - for continuous variables 3) plot(data$x,data$y) - to compare variables (ggplot is fine if you are comfortable with it) 4) cor(data$x,data$y) - to see a correlation between two variables

This presentation provides a comprehensive overview of Simple Linear Regression, covering both theoretical foundations and practical R implementation. Key topics include Ordinary Least Squares (OLS) estimation, interpreting the Coefficient of Determination R^2, and performing statistical inference on model coefficients. The slides also demonstrate how to validate model assumptions through residual diagnostics and provide a real-world example using study hours to predict exam scores.

An explanation of point estimates.

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Question2

Linear Regression in Cancer Data

ioslides presentation on simple linear regression